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基于 DMSP-OLS 和 NPP-VIIRS 夜间灯光遥感数据的新疆能源碳排放时空变化。

Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.

机构信息

College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China.

College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China.

出版信息

PLoS One. 2024 Oct 25;19(10):e0312388. doi: 10.1371/journal.pone.0312388. eCollection 2024.

Abstract

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

摘要

随着新疆维吾尔自治区(新疆)经济的快速发展,能源消耗成为碳排放的主要来源。在短期内,能源消耗和以煤为主的能源结构的增长趋势不太可能发生重大变化,这意味着碳排放预计将继续上升。为了阐明过去 15 年新疆能源相关碳排放的变化,本文整合了 DMSP/OLS 和 NPP/VIIRS 数据,从 2005 年到 2020 年生成了长期夜间灯光遥感数据。该数据用于分析碳排放的分布特征、空间自相关、变化频率和标准差椭圆。结果表明:(1)从 2005 年到 2020 年,新疆的总碳排放量持续增长,尽管增长率波动较大,但城市地区的碳排放量有所增加。在空间分布上,非碳排放量地区主要位于西北部;低碳排放量地区主要是中小城镇;高碳排放量地区集中在省会和城市群周围。(2)碳排放存在明显的区域差异,能源消耗具有明显的空间集聚性。聚类稳定,呈现出明显的“高高”和“低低”模式。(3)中心城市的碳排放量保持稳定,而省会和重点城市周边地区的变化频率更高。碳排放量的中心向东南方向转移,但后来有向西北方向移动的趋势。(4)碳排放的时空变化与能源消费强度、人口规模和经济增长密切相关。这些发现为制定差异化的碳排放目标和策略、优化能源结构、促进产业转型,实现新疆低碳经济发展提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6122/11508071/7147c17a3275/pone.0312388.g001.jpg

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